6 citations · 17 across the 4 of their papers we have counts for
5 papers
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Zhanke Zhou, Chenyu Zhou, Xuan Li +3
Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored. To close this gap, we perform the f…
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
Xin He, Jiangchao Yao, Yuxin Wang +5
One-shot neural architecture search (NAS) substantially improves the search efficiency by training one supernet to estimate the performance of every possible child architecture (i.…
Click-through Rate Prediction with Auto-Quantized Contrastive Learning
Yujie Pan, Jiangchao Yao, Bo Han +3
Click-through rate (CTR) prediction becomes indispensable in ubiquitous web recommendation applications. Nevertheless, the current methods are struggling under the cold-start scena…
MC-SF: Slow-Fast Learning for Mobile-Cloud Collaborative Recommendation
Zeyuan Chen, Jiangchao Yao, Feng Wang +4
With the hardware development of mobile devices, it is possible to build the recommendation models on the mobile side to utilize the fine-grained features and the real-time feedbac…
Device-Cloud Collaborative Learning for Recommendation
Jiangchao Yao, Feng Wang, KunYang Jia +3
With the rapid development of storage and computing power on mobile devices, it becomes critical and popular to deploy models on devices to save onerous communication latencies and…